Invention Publication
- Patent Title: PEROVSKITE SYNTHESIZABILITY PREDICTION METHOD USING GRAPH CONVOLUTIONAL NEURAL NETWORKS AND POSITIVE UNLABELED LEARNING
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Application No.: US18091877Application Date: 2022-12-30
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Publication No.: US20240135168A1Publication Date: 2024-04-25
- Inventor: You Sung JUNG , Geun Ho GU , Ju Hwan NOH , Ji Don JANG
- Applicant: KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY
- Applicant Address: KR Daejeon
- Assignee: KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY
- Current Assignee: KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY
- Current Assignee Address: KR Daejeon
- Priority: KR 20220134516 2022.10.18
- Main IPC: G06N3/08
- IPC: G06N3/08

Abstract:
Provided is a method for predicting perovskite synthesizability using a graph convolutional neural network and positive unlabeled learning, capable of predicting perovskite synthesizability by using a graph convolutional neutral network and positive unlabeled learning which is semi-supervised learning based on a labeled model using positive data and positive unlabeled data.
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